Copy-Move forgery detection using EOA, DWT and DCT

Copy-move forgery (CMF) is a new challenge because it reduces the accuracy of image forgery detection. In CMFD, we have selected and pasted similar points. The proposed method based on the Equilibrium Optimization Algorithm (EOA), Discrete Wavelet Transform (DWT), and Discrete Cosine Transform (DCT) helps image forgery detection. The method includes feature detection, image segmentation, and detection of forgery areas using the EOA, DWT, and DCT. In the first step, the image converts to a grayscale. Then, with the help of a discrete cosine transform algorithm, it is taken to the signal domain. With the help of discrete wavelet transform, its appropriate properties are introduced. In the next step, the image is divided into blocks of equal size. Then the similarity search is performed with the help of an equilibrium optimization algorithm and a suitable proportion function. Copy-move forgery detection using the Equilibrium Optimization Algorithm can find areas of forgery with a precision of about 86.21% for the IMD data set and about 83.98% for the MICC-F600 data set.